Open source hybrid-search projects
Every project in the registry tagged hybrid-search, ranked by real GitHub adoption.
Lightning-fast search for your applications
Fast, scalable vector database for AI applications
XERJ is the new way for AI to search data. Its autoindex capability activates agents to know your data without the token waste of grep and sed. One command inde
AI-native vector database for intuitive applications
One Postgres for your application data, full-text search, vector retrieval, and aggregations. Home of the pg_search extension.
The AI-native database built for LLM applications, providing incredibly fast hybrid search of dense vector, sparse vector, tensor (multi-vector), and full-text.
Enterprise workplace AI with data you own and control
Distributed vector search for AI-native applications
Full-text search API with real-time indexing and crawling
A multi-modal vector database that supports upserts and vector queries using unified SQL (MySQL-Compatible) on structured and unstructured data, while meeting t
中文优先的企业 RAG 知识库:可控解析、治理、切块、混合检索、重排、引用、图谱、评测与 Dify 接入。
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Frequently asked questions
How many open source hybrid-search projects are there?
This registry tracks 11 projects tagged hybrid-search, with 155,583 GitHub stars between them. The most-adopted is Meilisearch at 59,758 stars.
Are these hybrid-search projects free to use?
Yes — 9 of the 11 carry an explicit open-source licence across 2 distinct licences, so there is no licence fee. Where a project also sells a hosted or enterprise version, the self-hosted path remains free.
Which hybrid-search project should I choose?
The list above is ranked by GitHub stars, but stars measure attention rather than fit. Check three things on each card: the licence (permissive versus copyleft), the language it is written in, and the last-push date — a high-star project that has not been pushed in a year is a liability.
Are these hybrid-search projects still maintained?
10 of the 11 were pushed in the last 90 days, and every card shows its exact last-push date so you can see the rest. Sort your shortlist by that date before committing to a migration.